Wireless Compressive Sensing for Energy Harvesting Sensor Nodes

The authors consider the scenario in which multiple sensors send spatially correlated data to a Fusion Center (FC) via independent Rayleigh-fading channels with additive noise. Assuming that the sensor data is sparse in some basis, they show that the recovery of this sparse signal can be formulated as a Compressive Sensing (CS) problem. To model the scenario in which the sensors operate with intermittently available energy that is harvested from the environment, they propose that each sensor transmits independently with some probability, and adapts the transmit power to its harvested energy.